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Identifying relevant sources for data linking using a semantic web index

Nikolov, Andriy and d'Aquin, Mathieu (2011). Identifying relevant sources for data linking using a semantic web index. In: WWW2011 Workshop: Linked Data on the Web (LDOW 2011) at 20th International World Wide Web Conference (WWW 2011), 29 March 2011, Hyderabad, India.

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Abstract

With more data repositories constantly being published on the Web, choosing appropriate data sources to interlink with newly published datasets becomes a non-trivial problem. While catalogs of data repositories and meta-level descriptors such as VoiD provide valuable information to take these decisions, more detailed information about the instances included into repositories is often required to assess the relevance of datasets and the part of the dataset to link to. However, retrieving and processing such information for a potentially large number of datasets is practically unfeasible. In this paper, we examine how using an existing semantic web index can help identifying candidate datasets for linking. We further apply ontology schema matching techniques to rank these candidate datasets and extract the sub-dataset to use for linking, in the form of classes with instances more likely to match the ones of the local dataset.

Item Type: Conference Item
Copyright Holders: The Author/owner(s)
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetEC 7th Framework Programme, in the context of the SmartProducts project (231204)
Keywords: data fusion; data linking; linked data
Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 29298
Depositing User: Kay Dave
Date Deposited: 25 Aug 2011 15:41
Last Modified: 24 Oct 2012 08:07
URI: http://oro.open.ac.uk/id/eprint/29298
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